Jobs / United States / Waymo LLC
Senior Technical Program Manager, Simulation
Waymo LLC · 🇺🇸 Mountain View, CA, US; San Francisco, CA , US
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 290 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 87 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Waymo LLC paid sponsored hires in similar roles1 certified filing for “Technical Program Manager, Commercialization” (Architectural and Engineering Managers) in CA: $270k–$270k, median $270k. Most were filed at wage level IV (100%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
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Sponsor Radar — Waymo LLC
The US Department of Labor certified 290 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 87 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Waymo LLC →
About the role
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Waymo’s Technical Program Managers and Program Managers are accountable for Waymo’s roadmap execution by providing thoughtful cross-functional planning, clarity, and proactive risk management. In the face of complex technical and operational challenges with no established playbooks to follow, we act with thoughtful urgency, driving conversations, discussions, and outcomes. Our team partners closely with every function of Waymo to structure, own and drive work towards real-world deployments of the Waymo Driver across platforms and geographies. This role follows a hybrid work schedule and reports and you will report to a Director of Technical Program Management. You will: • Program Execution: Own and drive the execution of large, cross functional programs within the Simulation and ML Evaluation domain, translating technical roadmaps into structured project plans • ML Integration : Drive the execution of programs that integrate simulation deeply into the ML development loop, establishing a seamless, reliable path for model training, offline evaluation, and validation • Dependency & Risk Management : Proactively identify, track, and mitigate technical dependencies, risks, and blockers across onboard software and offboard infrastructure teams • Technical Judgment: Exercise strong technical judgment to contribute to tool/platform design discussions, evaluate architectural trade offs, and ensure deliverable quality • Operations & Release Coordination : Coordinate releases, manage tool deployment, and oversee triage workflows for simulation platforms to ensure high reliability and usability for developer teams • Process Scaling: Identify systemic bottlenecks in the offline evaluation loop and implement process or tooling improvements to scale simulation capabilities and efficiency You have: • Education : Bachelor's degree in Computer Science, Engineering, or a related technical field, or equivalent practical experience • TPM Experience : 3+ years of experience as a Technical Program Manager in a software engineering or large scale infrastructure environment • ML Experience: 2+ years of experience managing technical projects involving machine learning infrastructure, model training/evaluation loops, or ML data pipelines • Program Ownership : Proven track record of owning and driving complex technical programs end-to-end, managing timelines, risks, and dependencies across multiple stakeholders • Technical Judgment : Strong technical judgment with the ability to engage in design discussions with engineering leads and analyze technical trade offs • Communication : Excellent communication and interpersonal skills, with the ability to convey complex technical concepts to both research and infrastructure teams We prefer: • MLOps & Tooling: Experience with ML frameworks (JAX, PyTorch) and cloud based ML training/evaluation platforms • ML Based Simulation : Familiarity with advanced simulation technologies, including ML based scene generation (e.g. NeRF, Gaussian Splatting, Diffusion, etc.) and reactive agent modeling • Simulation: Familiar